Author ORCID Identifier

https://orcid.org/0000-0002-8358-2258

Document Type

Conference Paper

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

Computer Sciences, Information Science

Publication Details

IEEE LANMAN 2022

Abstract

There are various open testbeds available for testing algorithms and prototypes, including the Fed4Fire testbeds. This demo paper illustrates how the GPULAB Fed4Fire testbed can be used to test an edge-cloud model that employs an ensemble machine learning algorithm for detecting attacks on the Internet of Things (IoT). We compare experimentation times and other performance metrics of our model based on different characteristics of the testbed, such as GPU model, CPU speed, and memory. Our goal is to demonstrate how an edge-computing model can be run on the GPULab testbed. Results indicate that this use case can be deployed seamlessly on the GPULAB testbed.

DOI

https://doi.org/10.1109/LANMAN54755.2022.9820006

Funder

NGIAtlantic H2020 project under agreement no. OC3-292


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